A1156
Title: Investigating brain functional connectome using regularized blind source separation
Authors: Ying Guo - Emory University (United States) [presenting]
Abstract: Brain connectomics has become increasingly important in neuroimaging studies to advance understanding of neural circuits and their association with neurodevelopment, aging and brain disorders. A regularized blind source separation (BSS) framework is presented for reliable mapping of neural circuits underlying static and dynamic brain functional connectome. Using statistical techniques, the proposed framework achieves efficient and reliable mapping of connectivity traits underlying the static and dynamic brain functional connectome, characterizes temporal expressions and interactions of the connectivity traits that contribute to the reconfiguration of the observed dynamic functional connectivity, generates parsimonious and interpretable results in identifying whole-brain connectivity states and identifies connectivity traits associated with demographic attributes and behavioral measures. It is shown that the findings derived from the analyses demonstrate promising reliability and reproductivity across different analytical methods, subject resampling and different studies.
